Style Generalization

Style Generalization refers to the ability in the field of computer vision to use deep learning techniques so that models can generalize diverse style representations from a limited set of style samples, thereby generating high-quality images under different scenarios. The aim is to enhance the adaptability and robustness of the model, achieving cross-domain style transfer and increasing image diversity. This technology holds significant value in applications such as image processing, artistic creation, and virtual reality.